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Evaluating the variability of photovoltaics: A new stochastic method to generate site-specific synthetic solar data and applications to system studies

Tang, Yuchen, Cheng, John W.M., Duan, Qinwei, Lee, Cheuk Wing, Zhong, Jin
Renewable energy 2019 v.133 pp. 1099-1107
case studies, models, solar energy, stochastic processes, China
The power output of solar photovoltaics (PV) may have sharp fluctuations and its impact has to be carefully evaluated before integrating significant PV facilities into the power grid. Variability of solar resources is best measured by ground-based measurements. However, distributed ground-measured solar data is not available everywhere, and it would take considerable cost and time to obtain such data. Therefore, it is important and beneficial to model and estimate the variability of distributed PV generation even with insufficient solar data at each location. This study proposes a new methodology to generate spatially-distributed synthetic PV data based on detailed ground measurements collected at a few sites. The synthetic PV data is examined with specific criteria and the feasibility for simulating spatially-distributed PV generation is verified. A case study for Hong Kong is conducted using both the real and synthetic solar data. It is demonstrated that individual PV facilities can have significant fluctuations on a minute-by-minute basis, but the fluctuations can be significantly reduced if PV facilities are more spatially-distributed. The improvement to the estimation of solar variability with the proposed method is illustrated and the significance of its applications is discussed.